An adaptive parallel query processing middleware for the Grid

Grid services provide an important abstract layer on top of heterogeneous components (hardware and software) that take part in a Grid environment. In this scenario, applications such as scientific visualization require access to data of non-conventional data types, such as fluid path geometry, and the evaluation of special user programs and algebraic operators, such as spatial hash-join, on these data. In order to support such applications we are developing a Configurable Data Integration Middleware System for the Grid (CoDIMS-G). CoDIMS-G provides a query execution environment adapted to the heterogeneity and variations found in a Grid environment by offering a node scheduling algorithm and an adaptive query execution strategy. The latter both adapts to performance variations in a scheduled node and deals efficiently with repetitive evaluation of a query execution plan fragment, as needed for computing a particle's, trajectory. Copyright (c) 2005 John Wiley & Sons, Ltd.